Kernel-based error bounds of bilinear Koopman surrogate models for nonlinear data-driven control. IEEE Control Systems Letters, (9):1892-1897, 2025. [PUMA: EXC2075 PN4 PN4-2 PN4-2(II) inReview]
Koopman-based control using sum-of-squares optimization: Improved stability guarantees and data efficiency. European Journal of Control, 101286, 2025. [PUMA: EXC2075 PN4 PN4-2 PN4-2(II) inReview]
Koopman-based control of nonlinear systems with closed-loop guarantees. at - Automatisierungstechnik, (73)6:413--428, 2025. [PUMA: EXC2075 PN4 PN4-2 PN4-2(II) inReview]
Data-driven MPC with terminal conditions in the Koopman framework. Proc. 63rd IEEE Conference on Decision and Control (CDC), 146-151, Milan, Italy, 2024. [PUMA: EXC2075 PN4 PN4-2 PN4-2(II) curated]
Koopman-based feedback design with stability guarantees. IEEE Transactions on Automatic Control, (70)1:355-370, 2025. [PUMA: EXC2075 PN4 PN4-2 PN4-2(II) curated]
Decrypting Nonlinearity: Koopman Interpretation and Analysis of Cryptosystems. Automatica, (173):112022, 2025. [PUMA: EXC2075 PN4 PN4-2 PN4-2(II) curated]
Data-Driven System Analysis of Nonlinear Systems Using Polynomial Approximation. IEEE Transactions on Automatic Control, (69)7:4261-4274, 2024. [PUMA: PN4 PN4-2(II) EXC2075]
Control of bilinear systems using gain-scheduling: Stability and performance guarantees. 62nd IEEE Conference on Decision and Control (CDC), 4674-4681, Singapore, Singapore, 2023. [PUMA: EXC2075 PN4 PN4-2(II) curated]
A provably convergent control closure scheme for the Method of Moments of the Chemical Master Equation. Journal of Chemical Theory and Computation, (19)24:9049–9059, ACS Publications, December 2023. [PUMA: EXC2075 PN2 PN2-1B PN2-9 PN4 PN4-2(II) curated] URL
Guarantees for data-driven control of nonlinear systems using semidefinite programming: A survey. Annual Reviews in Control, (56):100911, 2023. [PUMA: EXC2075 PN4 PN4-2(II) curated]
Robust data-driven control for nonlinear systems using the Koopman operator. Proc. 22nd IFAC World Congress, (56)2:2257-2262, 2023. [PUMA: EXC2075 PN4 PN4-2(II) curated]
Gaussian inference for data-driven state-feedback design of nonlinear systems. 22nd IFAC World Congress, 4796-4803, 2023. [PUMA: EXC2075 PN4 PN4-2(II) curated]
Data-driven system analysis of nonlinear systems using polynomial approximation. IEEE Trans. Automat. Control (early access), 2023. [PUMA: EXC2075 PN4 PN4-2(II) curated]
Data-driven system analysis of nonlinear systems using polynomial approximation. IEEE Trans. Automat. Control, DOI: 10.1109/TAC.2023.3321212 (early access), 2022. [PUMA: EXC2075 PN4 PN4-2(II) curated]
Gaussian inference for data-driven state-feedback design of nonlinear systems. 22nd IFAC World Congress (accepted), Preprint: arXiv:2211.05639, 22nd IFAC World Congress (accepted), Preprint: arXiv:2211.05639, 2022. [PUMA: EXC2075 PN4 PN4-2(II) curated]
Guarantees for data-driven control of nonlinear systems using semidefinite programming: A survey. Annual Reviews in Control (submitted), Preprint: arXiv:2306.16042, 2023. [PUMA: EXC2075 PN4 PN4-2(II) curated]
Data-driven inference on optimal input-output properties of polynomial systems with focus on nonlinearity measures. IEEE Trans. Automat. Control, (68)5:2832 - 2847, 2023. [PUMA: EXC2075 PN4 PN4-2(II) curated merged]
Determining dissipativity for nonlinear systems from noisy data using Taylor polynomial approximation. Proc. American Control Conf. (ACC), 1432-1437, Atlanta, GA, USA, 2022. [PUMA: EXC2075 PN4 PN4-2 PN4-2(II) curated]